E-Discovery

This course explores the procedures associated with e-discovery. Students gain a comprehensive understanding of the Electronic Discovery Reference Model (EDRM) and electronically stored information (ESI) fundamentals and the opportunity to build practical e-discovery paralegal skills. Topics include the pre-trial litigation process and the forms and phases of general discovery.

This class will help students develop a comprehensive understanding of the early phases of the EDRM (Information Governance through Processing). Students will focus on the communication skills and paperwork needed to keep necessary parties informed. This class is designed to help students begin to manage e-discovery projects for a law firm.

This class provides students with an opportunity to develop and practice skills relating to the latter stages of the Electronic Discovery Reference Model (EDRM) framework using actual eDiscovery software that is used in the legal profession. Students will gain hands-on eDiscovery experience and learn best practices related to eDiscovery workflow and projects.

This class will help students develop a comprehensive understanding of the early phases of the EDRM (Information Governance through Processing). Students will focus on the communication skills and paperwork needed to keep necessary parties informed. This class is designed to help students begin to manage e-discovery projects for a law firm.

This class provides students an opportunity to develop and practice skills relating to the latter stages of the Electronic Discovery Reference Model (EDRM) framework using the E-Discovery Lab for Software, Simulation, and Applications (ELSSA).

This course focuses on essential productivity applications. Students will explore tools and methods essential to modern paralegal tasks and will learn the importance of databases to E-Discovery applications. Topics include data analysis, indexing, and database structures.

This course is designed to develop advanced skills in utilities and applications used in the litigation support and legal industry. Students in this class will use software applications in Bryan University's E-Discovery Lab for Software, Simulation, and Applications (ELSSA).

This course will introduce students to analytics technologies designed to make document review and analysis more efficient. Students will gain experience with data analytics tools and gain a general understanding of technology assisted review or predictive coding, and the tools and processes associated with machine learning and the auto- categorization of documents.

Students will learn the fundamental principles of traditional project management and how to apply these principles to the management of an e-discovery project. Students will work within a process framework using methodology to effectively manage the scope, time, and cost of an electronic discovery project.